Poll the status of an ongoing research task.
AI agents call research_poll to retrieve information from NotebookLM MCP Server without modifying anything — typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.
This tool only reads/queries the status of an existing research task. It has no side effects, does not modify data, and does not trigger any operations. It is a straightforward read operation, making it low severity with high confidence.
From the tool's definition Tool description states 'Poll the status of an ongoing research task' — a query operation that retrieves status information without modifying, deleting, or executing any actions.
Attacks that exploit this kind of access
Poll the status of an ongoing research task. It is categorised as a Read tool in the NotebookLM MCP Server MCP Server, which means it retrieves data without modifying state.
Register the NotebookLM MCP Server MCP server in PolicyLayer and add a rule for research_poll: allow, deny, rate-limit, or require approval. Point your MCP client at the PolicyLayer proxy URL and the rule is enforced on every call, before it reaches NotebookLM MCP Server. Nothing to install.
research_poll is a Read tool with low risk. Read-only tools are generally safe to allow by default.
Yes. Add a rate_limit block to the research_poll rule in your PolicyLayer policy. For example, setting max: 10 and window: 60 limits the tool to 10 calls per minute. Rate limits are tracked per agent session and reset automatically.
Set action: deny in the PolicyLayer policy for research_poll. The AI agent will receive a policy violation error and cannot call the tool. You can also include a reason field to explain why the tool is blocked.
research_poll is provided by the NotebookLM MCP Server MCP server (pavelguzenfeld/notebooklm-mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Every MCP server has a record like this.
Type a name, get the same breakdown: verified identity, auth posture, risk grade, capabilities, recommended policy.
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